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Assessing the Formation of Experience-Based Gender Expectations in an Implicit Learning Scenario

机译:评估内隐学习场景中基于经验的性别期望的形成

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摘要

The present study investigates the formation of new word-referent associations in an implicit learning scenario, using a gender-coded artificial language with spoken words and visual referents. Previous research has shown that when participants are explicitly instructed about the gender-coding system underlying an artificial lexicon, they monitor the frequency of exposure to male vs. female referents within this lexicon, and subsequently use this probabilistic information to predict the gender of an upcoming referent. In an explicit learning scenario, the auditory and visual gender cues are necessarily highlighted prior to acqusition, and the effects previously observed may therefore depend on participants' overt awareness of these cues. To assess whether the formation of experience-based expectations is dependent on explicit awareness of the underlying coding system, we present data from an experiment in which gender-coding was acquired implicitly, thereby reducing the likelihood that visual and auditory gender cues are used strategically during acquisition. Results show that even if the gender coding system was not perfectly mastered (as reflected in the number of gender coding errors), participants develop frequency based expectations comparable to those previously observed in an explicit learning scenario. In line with previous findings, participants are quicker at recognizing a referent whose gender is consistent with an induced expectation than one whose gender is inconsistent with an induced expectation. At the same time however, eyetracking data suggest that these expectations may surface earlier in an implicit learning scenario. These findings suggest that experience-based expectations are robust against manner of acquisition, and contribute to understanding why similar expectations observed in the activation of stereotypes during the processing of natural language stimuli are difficult or impossible to suppress.
机译:本研究调查了在隐性学习场景中新的单词指称联想的形成,使用带有语音单词和视觉对象的性别编码人工语言。先前的研究表明,当明确指示参与者有关人工词典基础的性别编码系统时,他们会监视该词典中男性与女性被指接触的频率,随后使用此概率信息来预测即将到来的性别指称对象。在一个明确的学习场景中,在习得之前必须突出听觉和视觉上的性别暗示,因此先前观察到的效果可能取决于参与者对这些暗示的明显了解。为了评估基于经验的期望的形成是否依赖于对底层编码系统的明确了解,我们提供了一项实验数据,该实验隐含了性别编码,从而降低了视觉和听觉性别暗示在策略性使用过程中的可能性收购。结果表明,即使未完全掌握性别编码系统(反映在性别编码错误的数量中),参与者仍会产生基于频率的期望,该期望与先前在明确学习场景中观察到的期望相当。与以前的发现一致,参与者比性别与诱导的期望不一致的对象更快地识别出性别与诱导的期望相符的对象。但是,与此同时,眼动数据表明,这些期望可能会在隐性学习场景中更早地浮出水面。这些发现表明,基于经验的期望对习得方式具有鲁棒性,并且有助于理解为什么在自然语言刺激的处理过程中,刻板印象激活过程中观察到的相似期望难以或无法被抑制。

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